research
Deep research with parallel sub-agents, query classification, and filesystem artifact passing
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Deep research with parallel sub-agents, query classification, and filesystem artifact passing
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Run dead-code and duplicate-code detection across the codebase, get categorized cleanup recommendations
Review the current diff for correctness bugs and spec drift, then emit an evidence-oriented findings list
Execute a plan file step-by-step with progress tracking and phase checkpoints
Initialize a session by executing the cross-agent New Sessions protocol declared in AGENTS.md.
Modularize large CLAUDE.md files with path-scoped rules and doc extraction
One-time contributor setup. Install spec-spine and verify the governed loop (compile, index check, lint, couple) so /init can report lifecycle and structural counts.
| name | research |
| description | Deep research with parallel sub-agents, query classification, and filesystem artifact passing |
| allowed-tools | Task, Read, Write, Bash(git log:*), Bash(git diff:*), WebSearch, WebFetch, Glob, Grep |
| argument-hint | <question or topic to investigate> |
Conduct deep, parallel research on a topic using multiple specialized sub-agents.
$ARGUMENTS
This is the critical first step. Classify before doing anything else.
| Type | Characteristics | Sub-agents | Depth per agent |
|---|---|---|---|
| Breadth-first | Multiple independent aspects, surveys, comparisons | 5-10 | 5-10 searches each |
| Depth-first | Single topic requiring thorough understanding, technical deep-dives | 2-4 | 10-15 searches each |
| Simple factual | Single fact, specific data point, quick lookup | 1-2 | 3-5 searches each |
After reading the query, determine:
Spawn all sub-agents in a single message for true parallelization using the Task tool.
Each Task prompt MUST begin with a depth-mode trigger phrase:
| Mode | Trigger prefix | Expected effort |
|---|---|---|
| Quick verification | "Quick check:", "Verify:", "Confirm:" | 3-5 searches |
| Focused investigation | "Investigate:", "Explore:", "Find details about:" | 5-10 searches |
| Deep research | "Deep dive:", "Comprehensive:", "Thorough research:" | 10-15 searches |
Each sub-agent MUST:
/tmp/research_[timestamp]_[topic_slug].mdThis reduces token usage by approximately 90% compared to passing full reports inline.
Breadth-first ("Compare approach A vs approach B vs approach C"):
Task 1: "Investigate: approach A architecture, performance characteristics, and ecosystem maturity"
Task 2: "Investigate: approach B architecture, performance characteristics, and ecosystem maturity"
Task 3: "Investigate: approach C architecture, performance characteristics, and ecosystem maturity"
Task 4: "Explore: performance benchmarks comparing the three approaches"
Task 5: "Investigate: developer experience, tooling, and community size for each"
Task 6: "Quick check: latest release dates and roadmap status for each"
Depth-first ("How does the spec compiler validation pipeline work?"):
Task 1: "Deep dive: trace the spec compiler entry point through all validation phases (codebase research using Grep/Read)"
Task 2: "Comprehensive: map all error codes and validation rules in the spec compiler"
Task 3: "Thorough research: document the data flow and intermediate representations used during compilation"
Simple factual ("What license does this project use?"):
Task 1: "Quick check: find the LICENSE file and any license declarations in package manifests"
After all sub-agents complete:
/tmp/research_*.md paths from sub-agent responses./tmp/research_final_[timestamp].md.# Research Report: [Query Topic]
## Executive Summary
[3-5 paragraph overview synthesizing all findings]
## Key Findings
1. **[Finding 1]**: synthesized from multiple sub-agent reports
2. **[Finding 2]**: cross-referenced and verified
3. **[Finding 3]**: with supporting evidence
## Detailed Analysis
### [Theme 1]
[Comprehensive synthesis from all relevant sub-agent findings]
### [Theme 2]
[Comprehensive synthesis from all relevant sub-agent findings]
## Sources and References
[Consolidated list organized by type: codebase files, documentation, web sources]
## Research Metadata
- Query classification: [breadth / depth / simple]
- Sub-agents deployed: [count and focus areas]
- Total sources analyzed: [count]
- Research artifacts: [list of /tmp/research_*.md files]
Now classify the query and launch parallel research sub-agents.